Retrieval of Land Surface Temperature from Earth Observation Satellites for Gas Flaring Sites in the Niger Delta, Nigeria

Barnabas Morakinyo; Samantha Lavender; Victor Abbott

doi:doi:10.11648/j.ijema.20200803.13

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Retrieval of Land Surface Temperature from Earth Observation Satellites for Gas Flaring Sites in the Niger Delta, Nigeria

Barnabas Morakinyo, Samantha Lavender, Victor Abbott

Published in International Journal of Environmental Monitoring and Analysis (Volume 8, Issue 3)

Received: 31 January 2020 Accepted: 3 March 2020 Published: 27 August 2020

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Abstract

This research investigates the recording of Land Surface Temperature (LST) by Earth Observation (EO) Satellites for four gas flaring sites in Rivers State, Nigeria. Six Landsat 5 Thematic Mapper (TM) and Eleven Landsat 7 Enhanced Thematic Mapper Plus (ETM+) from 17 January 1986 to 08 March 2013 with < 5% cloud contamination were considered. All the sites are located within a single Landsat scene (Path 188, Row 057). Dark Object Subtraction (DOS) method and Atmospheric Correction Parameter (ATMCORR) Calculator were used to obtain atmospheric correction effects parameters for multispectral and thermal bands [Upwelling radiance (L_u), downwelling radiance (L_d) and transmittance (τ)] of Landsat data respectively. The emissivity (ε) for each site is estimated by using standard values for determined land surface cover from Look Up Table (LUT). The correction obtained from DOS method was applied to the computed reflectance to get the atmospherically corrected reflectance that was used for the classification of land cover. The L_u, L_d and τ obtained were applied to the calibrated at-sensor radiance band 6 (high gain) data to compute the surface-leaving radiance (L_λ) with the εvalues obtained for each site. The Planck equation was inverted using the calibration constants to derive LST. Six range of LST values were retrieved for each flaring site, with Bonny Liquefied Natural Gas (LNG) Plant recorded the highest LST (345.0 K) and Umudioga Flow Station with the lowest (293.0 K). LST retrieved from both sensors for the flare hotspots are the highest values compared to other locations within the processing sites, which was clearly shown through Geospatial Information System (GIS) spatial analysis and the transects plots. Furthermore, the closer is the distance to the flare, the higher is the temperature and vice versa. Based on these results, it can be concluded that satellite based sensors, such as Landsat TM and ETM+, have the ability to record LST at gas flaring sites in the Niger Delta.

Published in	International Journal of Environmental Monitoring and Analysis (Volume 8, Issue 3)
DOI	10.11648/j.ijema.20200803.13
Page(s)	59-74
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

Retrieval, Earth Observation (EO) Satellites, Gas Flaring, Land Surface Temperature (LST), Niger Delta

References

[1]	Jiménez-Muñoz, J. C., Sobrino, J. A., El-Kharraz, J., Gómez, M., Romaguera, M and Sòria, G. (2003). "Synergistic use of DAIS bands to retrieve land surface emissivity and temperature". IGARSS 2003: IEEE International Geoscience and Remote Sensing Symposium, Vols. I-VII, Proceedings: 1062-1064.
[2]	Valor, E and Caselles, V. (1996). "Mapping land surface emissivity from NDVI: Application to European, African, and South American areas”. Remote Sensing of Environment 57 (3): 167-184.
[3]	Kalnay, E and Cai, M. (2003). “Impact of Urbanization and Land-use Change on Climate”. Nature, 423: 528-531.
[4]	Wan, Z., Wang, P and Li, X. (2004). “Using MODIS Land Surface Temperature and Normalized Difference Vegetation Index Products for Monitoring Drought in the Southern Great Plains, USA”. International Journal of Remote Sensing 25: 61-72.
[5]	Chapin, F., Sturm, M., Serreze, M., McFadden, J., Key, J., Lloyd, A., McGuire, A., Rupp, T., Lynch, A and Schimel, J. (2005). “Role of Land-Surface Changes in Arctic Summer Warming”. Science 310: 657-660.
[6]	Qin, Q., Zhang, N., Nan, P and Chai, L. (2011). "Geothermal area detection using Landsat ETM+ thermal infrared data and its mechanistic analysis: A case study in Tengchong, China”. International Journal of Applied Earth Observation and GeoInformation 13: 552-559.
[7]	Akhoonadzadeh, M and Saradjian, M. R. (2008). "Comparison of Land Surface Temperature Mapping Using MODIS and ASTER Images in Semi-Arid Area". The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Science, Beijing 37 (Part B8).
[8]	Ramanathan, V., Crutzen, P., Kiehl, J and Rosenfeld, D. (2001). “Aerosols, Climate, and the Hydrological Cycle”. Science 294: 2119-2124.
[9]	Karnieli, A., Agam, N., Pinker, R. T., Anderson, M., Imhoff, M. L., Gutman, G. G., Panov, N and Goldberg, A. (2010). “Use of NDVI and Land Surface Temperature for Drought Assessment: Merits and Limitations”. Journal of Climatology, 23: 618-633.
[10]	Kustas, W and Anderson, M. (2009). “Advances in Thermal Infrared Remote Sensing for Land Surface Modeling”. Agric. For. Meteorology. 149: 2071-2081.
[11]	Agam, N., Kustas, W. P., Anderson, M. C., Li, F and Colaizzi, P. D. (2008). “Utility of Thermal Image Sharpening for Monitoring Field-Scale Evapotranspiration OverRainfed and Irrigated Agricultural Regions”. Geophysical Research Letters 35: L02402.
[12]	Li, Z., Tang, B., Wu, H., Ren, H., Yan, G., Wan, Z., Trigo, I. F and Sobrino, J. A. (2013).“Satellite-Derived Land Surface Temperature: Current Status and Perspectives”. Remote Sensing of Environment 131: 14-37.
[13]	NOAA. (2019). National Oceanic and Atmospheric Administration. “Advanced Very High Resolution Radiometer (AVHRR): Overview”. [Online]. Available: https://www.ngdc.noaa.gov/ecosys/cdroms/AVHRR97_d1/avhrr.htm [Accessed 15th June 2019].
[14]	NASA. (2019). National Aeronautics and Space Administration. “Landsat Science”. [Online]. Available: http://landsat.gsfc.nasa.gov/?p=3180 [Accessed 1st May 2019].
[15]	ESA. (2015). European Space Agency. “AATSR Product Handbook”, Issue 2.2, Italy. [Online]. Available: http: 380 www.earth.esa.int/pub/ESA_DOC/.../AATSR/aatsr.ProductHandbook.2_2.pdf [Accessed 24th October 2019].
[16]	USGS. (2019). United States Geological Survey. U.S. Department of the Interior. [Online]. Available: http://eros.usgs.gov/#/Find_Data/Products_and_Data_Available/ETM. [Accessed 19th June 2019].
[17]	Caseiro, A., Gehrke, B., Rücker, G., Leimbach, D and Johannes W. Kaiser, J. W. (2019). Gas flaring activity and black carbon emissions in 2017 derived from Sentinel-3A SLSTR. Earth System Science Data: 1-35.
[18]	Faruolo, M., Lacava, T., Pergola, N and Tramutoli, V. (2018). “On the Potential of the RST-FLARE Algorithm for Gas Flaring Characterization from Space. Sensors 18: 2466.
[19]	Fisher, D and Wooster, M. (2018). “Shortwave IR Adaptation of the Mid-Infrared Radiance Method of Fire Radiative Power (FRP) Retrieval for Assessing Industrial Gas Flaring Output”. International Journal of Remote Sensing 10: 305.
[20]	Morakinyo, B. O. (2015). “Flaring and Pollution Detection in the Niger Delta using Remote Sensing”. Ph.D Thesis, School of Marine Science and Engineering, University of Plymouth, Plymouth, United Kingdom.
[21]	Rozenstein, O., Qin, Z., Derimian, Y and Karnieli, A. (2014). “Derivation of Land Surface Temperature for Landsat-8 TIRS Using a Split Window Algorithm”. Sensors 14: 5768-5780; doi: 10.3390/s140405768.
[22]	Otukei, J. R and Blaschke, T. (2012). “You Know The Temperature at the Weather Station But Do You Know It Anywhere Else? Assessing Land Surface Temperature Using Landsat ETM+ Data”. In Proceedings of The first Conference on Advances in Geomatics Research. [Online]. Available: http://www.cedat.mak.ac.ug/wp-content/themes/CEDATTheme/Publications/You%20Know%20The%20Temperature%20at%20the%20Weather%20Station%20But%20Do%20You%20Know%20It%20Anywhere%20 Else_Assessing%20Land%20S.pdf [Accessed 17th June 2019].
[23]	Giannini, M. B., Belfiore, O. R., Parente, C and Santamaria, R. (2015). “Land Surface Temperature from Landsat 5 TM images: comparison of different methods using airborne thermal data”. Journal of Engineering Science and Technology Review 8 (3): 83-90.
[24]	Mao, K., Qin, Z., Shi, J and Gong, P. (2005). "A practical split-window algorithm for retrieving land surface temperature from MODIS data”. International Journal of Remote Sensing 26 (15): 3181-3204.
[25]	Qin, Z., Olmo, G. D and Karnieli, A. (2001). “Derivation of split window algorithm and its sensitivity analysis for retrieving land surface temperature from NOAA-advanced very high resolution radiometer data”. Geophysical Research: 22655-22 670.
[26]	Wan, Z and Dozier, J. (1996). “A generalized split-window algorithm for retrieving land-surface temperature from space” Geoscience and Remote Sensing, IEEE Transactions, 34 (4): 892-905.
[27]	Wan, Z. and Li, -L. (1997). ‘‘A physics-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data,’’ IEEE Trans. Geosci. Remote Sensing 35 (4): 980-996.
[28]	Wan, Z., Zhang, Y., Zhang, Q and Li, Z. (2004). “Quality assessment and validation of the MODIS global land surface temperature”. International Journal of Remote Sensing 25: 261-274.
[29]	Wan, Z. (2002). “Validation of the land-surface temperature products retrieved from Terra Moderate Resolution Imaging Spectroradiometer data”. Remote Sensing of Environment 83: 163-180.
[30]	Gillespie, A., Rokugawa, S., Matsunaga, T., Cothern, J. S., Hook, S. and Kahle, A. B. (1998). "A temperature and emissivity separation algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images". IEEE Transactions on Geoscience and Remote Sensing 36 (4): 1113-1126.
[31]	Sobrino, J. A., Li, Z. -L and Stoll, M. P. (1993). “Impact of the atmospheric transmittance and total water vapour content in the algorithms for estimating satellite sea temperature”. IEEE Transactions on Geoscience and Remote Sensing31: 946-952.
[32]	Harris, A. R and Mason, I. M. (1992). “An extension to the split-window technique giving improved atmospheric correction and total water vapour”. International Journal of Remote Sensing 13: 881-892.
[33]	Sobrino, J. A., Jiménez-Muñoz, J. C and Paolini, L. (2004). “Land surface temperature retrieval from LANDSAT TM 5”. Remote Sensing of Environment, 90 (4): 434-440.
[34]	Dung, E. J., Bombom, L. S. and Agusomu, T. D. (2008). "The effects of gas flaring on crops in the Niger Delta, Nigeria". GeoJournal 73: 297-305.
[35]	Nwaerema P., Ologunorisa, T. E., Nwagbara, M. O., Ojeh, V. N. (2019). “Geo-Spatial Dynamics of Land Surface Temperature of Port Harcourt Metropolis and Environs: Implication for Heat Disaster Management”. Earth Sciences. 8 (3): 169-177.
[36]	Nwaerema, P and Ajiere S. (2020). “Regional Mapping of Land Surface Temperature (LST), Land Surface Emissivity (LSE) and Normalized Difference Vegetation Index (NDVI) of South-South Coastal Settlements of Rivers State in Nigeria”. World News of Natural Sciences 28: 76-86.
[37]	Ayanlade, Y and Howard, M. T. (2019). “Land surface temperature and heat fluxes over three cities in Niger Delta”. Journal of African Earth Sciences 151: 54-66.
[38]	Liu, Y., Chao, S., Yang, Y., Zhou, M., Zhan, W and Cheng, W. (2016). “Automatic extraction of offshore platforms using time-series Landsat-8 Operational Land Imager data”. Remote Sensing of Environment 175: 73-91.
[39]	Anejionu, O. C. D., Blackburn, G. A Whyatt, J. D. (2015). “Detecting gas flares and estimating flaring volumes at individual flow stations using MODIS data”. Remote Sensing of Environment 158: 81-94.
[40]	Elvidge, C. D., Ziskin, D., Baugh, K. E., Tuttle, B. T., Ghosh, T., Pack, D. W., Erwin, E. H and Zhizhin, M. A. (2009). “A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data”. Energies 2: 595-622.
[41]	Showstack, R. (2007). “Satellite study of natural gas flaring. EOS Trans. American Journal of Geophysical Union 88.
[42]	Anejionu, O. C. D., Blackburn, G. A Whyatt, J. D. (2014). “Satellite survey of gas flares: Development and application of a Landsat based technique in the Niger Delta”. International Journal of Remote Sensing 35: 1900-1925.
[43]	Chowdhury, S., Shipman, T., Chao, D., Elvidge, C. D., Zhizhin, M and Hsu, F. C. (2014). “Daytime gas flare detection using Landsat-8 multispectral data”. In Proceedings of the IEEE International Geosciences of Remote Sensing Symposium, Quebec City, QC, Canada, 13-18 July pp. 258-261.
[44]	Google Earth. (2020). “Image showing Eleme Petroleum Refinery II Company, Bonny LNG, Obigbo Flow Station and Umudioga Flow Station.
[45]	Chander, G and Markham, K. (2003). “Revised Landsat-5 TM Radiometric Calibration Procedures and Post calibration Dynamic Ranges”. IEEE Transactions on Geoscience and Remote Sensing 41 (11): 2674-2677.
[46]	Chen, F., Zhao, X and Ye, H. (2012). “Making use of the Landsat 7 SLC-off ETM+ image through different recovering approaches”. Postgraduate Conference on Infrastructure and Environment (3rd IPCIE), vol. 2, pp. 557-563. [Online]. Available: http://dx.doi.org/10.5772/48535 [Accessed 26th February 2019].
[47]	NASA. (2002). National Aeronautics and Space Administration. “Landsat 7 ETM+ Science Data Users Handbook”. [Online]. Available: http://www.landsathandbook.gsfc.nasa.gov/data_prod/prog_sect11_3.html [Accessed 23rd August 2019].
[48]	Barsi, J. A., Schott, J. R., Palluconi, F. D and Hook, S. J. (2005). “Validation of a Web-Based Atmospheric Correction Tool for Single Thermal Band Instruments”. Earth Observing Systems X, Proceedings of SPIE Bellingham, WA, 2005.
[49]	Kaufman, Y. J., Karnieli, A and Tanre, D. (2000). "Detection of dust over deserts using satellite data in the solar wavelengths". IEEE Transactions on Geoscience and Remote Sensing 38: 525-531.
[50]	Liang, S., Fallah-Adl, H., Kalluri, S., JaJa, J., Kaufman, Y and Townshend, J. (1997). “Development of an operational atmospheric correction algorithm for TM imagery”. Journal of Geophysical Research 102: 17173-17186.
[51]	Liang, S., Fang, H. and Chen, M. (2001). "Atmospheric Correction of Landsat ETM+ Land Surface Imagery - Part I: Methods". IEEE Transactions on Geoscience and Remote Sensing 39 (11): 2490-2498.
[52]	Şatır, O and Berberoğlu, S. (2012). “Land Use/Cover Classification Techniques Using Optical Remotely Sensed Data in Landscape Planning”, Landscape Planning, Dr. Murat Ozyavuz (Ed.), ISBN: 978-953-51-0654-8, InTech. [Online]. Available: http://www.intechopen.com/books/landscapeplanning/land-use-cover-classificationtechniques-using-optical-remotelysensed-data-in-landscape-plannin [Accessed 15th September 2019].
[53]	Alvarez, J. (2009). “Land cover verification along Freeway Corridors, Natomas Basin Area, California, USA”. [Online]. Available: http://www.academic.emporia.edu/aberjame/student/alvarez4/natchange.htm l [Accessed 26th April 2019].
[54]	Morakinyo, B. O., Lavender, S., Schwarz, J. and Abbott, V. (2019). “Mapping of land cover and estimation of their emissivity values for gas flaring sites in the Niger Delta”. British Journal of Environmental Sciences 7 (2): 31-58.
[55]	Labed, J. and Stoll, M. P. (1991). "Spatial variability of land surface emissivity in the thermal infrared band: Spectral signature and effective surface temperature". Remote Sensing of Environment 38: 1-7.
[56]	Jin, M. and Liang, S. (2006). "An Improved Land Surface Emissivity Parameter for Land Surface Models Using Global Remote Sensing Observations". Journal of Climate 19: 2867-2881.
[57]	Humes, K. S., Kustas, W. P., Moran, M. S., Nichols, W. D. and Weltz, M. A. (1994). "Variability of emissivity and surface temperature over a sparsely vegetated surface". Water resources research 30 (5): 1299-1310.
[58]	Hipps, L. E. (1989). "The infrared emissivities of soil and Artemisia tridentate and subsequent temperature corrections in a shrub-steppe ecosystem". Remote Sensing of Environment 27: 337-342.
[59]	van de Griend, A. A., Owe, M., Groen, M. and Stoll, M. P. (1991). "Measurement and spatial variation of thermal infrared surface emissivity in a savanna environment”. Water Resources Research 27: 371-379.
[60]	Masuda, K., Takashima, T. and Takayama, Y. (1988). “Emissivity of Pure and Sea Waters for the Model Sea Surface in the Infrared Window Regions”. Remote Sensing of Environment 24: 313-329.
[61]	Stathopoulou, M. and Cartalis, C. (2007). "Daytime urban heat island from Landsat ETM+ and Corine land cover data: An application to major cities in Greece”. Solar Energy 81: 358-368.
[62]	Shore, D. (1996). "Making the flare safe”. Journal of Loss Prevention in the Process Industries 9 (6).
[63]	PTT. (2008). "Flaring and venting philosophy”. [Online]. Available: http://www.Scribd.com/doc/108536828/Flaring-and-Venting-Philosophy [Accessed 12th February 2019].
[64]	Sáez, A. (2010). "Industrial application of natural gas”. [Online]. Available: http://www.intechopen.com/books/natural-gas/industrial-applications-of-natural-gas [Accessed 1st March 2019].
[65]	Coll, C., Galve, J. M., Sanchez, J. M and Caselles, V. (2010). "Validation of Landsat - 7 ETM+ thermal-band calibration and atmospheric correction with ground-based measurement". IEEE Transaction on Geoscience and Remote Sensing 48 (1): 547-555.

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APA Style

Barnabas Morakinyo, Samantha Lavender, Victor Abbott. (2020). Retrieval of Land Surface Temperature from Earth Observation Satellites for Gas Flaring Sites in the Niger Delta, Nigeria. International Journal of Environmental Monitoring and Analysis, 8(3), 59-74. https://doi.org/10.11648/j.ijema.20200803.13

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ACS Style

Barnabas Morakinyo; Samantha Lavender; Victor Abbott. Retrieval of Land Surface Temperature from Earth Observation Satellites for Gas Flaring Sites in the Niger Delta, Nigeria. Int. J. Environ. Monit. Anal. 2020, 8(3), 59-74. doi: 10.11648/j.ijema.20200803.13

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Barnabas Morakinyo, Samantha Lavender, Victor Abbott. Retrieval of Land Surface Temperature from Earth Observation Satellites for Gas Flaring Sites in the Niger Delta, Nigeria. Int J Environ Monit Anal. 2020;8(3):59-74. doi: 10.11648/j.ijema.20200803.13

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@article{10.11648/j.ijema.20200803.13,
  author = {Barnabas Morakinyo and Samantha Lavender and Victor Abbott},
  title = {Retrieval of Land Surface Temperature from Earth Observation Satellites for Gas Flaring Sites in the Niger Delta, Nigeria},
  journal = {International Journal of Environmental Monitoring and Analysis},
  volume = {8},
  number = {3},
  pages = {59-74},
  doi = {10.11648/j.ijema.20200803.13},
  url = {https://doi.org/10.11648/j.ijema.20200803.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20200803.13},
  abstract = {This research investigates the recording of Land Surface Temperature (LST) by Earth Observation (EO) Satellites for four gas flaring sites in Rivers State, Nigeria. Six Landsat 5 Thematic Mapper (TM) and Eleven Landsat 7 Enhanced Thematic Mapper Plus (ETM+) from 17 January 1986 to 08 March 2013 with u), downwelling radiance (Ld) and transmittance (τ)] of Landsat data respectively. The emissivity (ε) for each site is estimated by using standard values for determined land surface cover from Look Up Table (LUT). The correction obtained from DOS method was applied to the computed reflectance to get the atmospherically corrected reflectance that was used for the classification of land cover. The Lu, Ld and τ obtained were applied to the calibrated at-sensor radiance band 6 (high gain) data to compute the surface-leaving radiance (Lλ) with the εvalues obtained for each site. The Planck equation was inverted using the calibration constants to derive LST. Six range of LST values were retrieved for each flaring site, with Bonny Liquefied Natural Gas (LNG) Plant recorded the highest LST (345.0 K) and Umudioga Flow Station with the lowest (293.0 K). LST retrieved from both sensors for the flare hotspots are the highest values compared to other locations within the processing sites, which was clearly shown through Geospatial Information System (GIS) spatial analysis and the transects plots. Furthermore, the closer is the distance to the flare, the higher is the temperature and vice versa. Based on these results, it can be concluded that satellite based sensors, such as Landsat TM and ETM+, have the ability to record LST at gas flaring sites in the Niger Delta.},
 year = {2020}
}

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TY  - JOUR
T1  - Retrieval of Land Surface Temperature from Earth Observation Satellites for Gas Flaring Sites in the Niger Delta, Nigeria
AU  - Barnabas Morakinyo
AU  - Samantha Lavender
AU  - Victor Abbott
Y1  - 2020/08/27
PY  - 2020
N1  - https://doi.org/10.11648/j.ijema.20200803.13
DO  - 10.11648/j.ijema.20200803.13
T2  - International Journal of Environmental Monitoring and Analysis
JF  - International Journal of Environmental Monitoring and Analysis
JO  - International Journal of Environmental Monitoring and Analysis
SP  - 59
EP  - 74
PB  - Science Publishing Group
SN  - 2328-7667
UR  - https://doi.org/10.11648/j.ijema.20200803.13
AB  - This research investigates the recording of Land Surface Temperature (LST) by Earth Observation (EO) Satellites for four gas flaring sites in Rivers State, Nigeria. Six Landsat 5 Thematic Mapper (TM) and Eleven Landsat 7 Enhanced Thematic Mapper Plus (ETM+) from 17 January 1986 to 08 March 2013 with u), downwelling radiance (Ld) and transmittance (τ)] of Landsat data respectively. The emissivity (ε) for each site is estimated by using standard values for determined land surface cover from Look Up Table (LUT). The correction obtained from DOS method was applied to the computed reflectance to get the atmospherically corrected reflectance that was used for the classification of land cover. The Lu, Ld and τ obtained were applied to the calibrated at-sensor radiance band 6 (high gain) data to compute the surface-leaving radiance (Lλ) with the εvalues obtained for each site. The Planck equation was inverted using the calibration constants to derive LST. Six range of LST values were retrieved for each flaring site, with Bonny Liquefied Natural Gas (LNG) Plant recorded the highest LST (345.0 K) and Umudioga Flow Station with the lowest (293.0 K). LST retrieved from both sensors for the flare hotspots are the highest values compared to other locations within the processing sites, which was clearly shown through Geospatial Information System (GIS) spatial analysis and the transects plots. Furthermore, the closer is the distance to the flare, the higher is the temperature and vice versa. Based on these results, it can be concluded that satellite based sensors, such as Landsat TM and ETM+, have the ability to record LST at gas flaring sites in the Niger Delta.
VL  - 8
IS  - 3
ER  -

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Author Information

Barnabas Morakinyo

Department of Surveying & Geoinformatics, Baze University, Abuja, Nigeria
Samantha Lavender

School of Marine Science & Engineering, University of Plymouth, Plymouth, UK
Victor Abbott

School of Marine Science & Engineering, University of Plymouth, Plymouth, UK

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Barnabas Morakinyo, Samantha Lavender, Victor Abbott. (2020). Retrieval of Land Surface Temperature from Earth Observation Satellites for Gas Flaring Sites in the Niger Delta, Nigeria. International Journal of Environmental Monitoring and Analysis, 8(3), 59-74. https://doi.org/10.11648/j.ijema.20200803.13

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ACS Style

Barnabas Morakinyo; Samantha Lavender; Victor Abbott. Retrieval of Land Surface Temperature from Earth Observation Satellites for Gas Flaring Sites in the Niger Delta, Nigeria. Int. J. Environ. Monit. Anal. 2020, 8(3), 59-74. doi: 10.11648/j.ijema.20200803.13

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AMA Style

Barnabas Morakinyo, Samantha Lavender, Victor Abbott. Retrieval of Land Surface Temperature from Earth Observation Satellites for Gas Flaring Sites in the Niger Delta, Nigeria. Int J Environ Monit Anal. 2020;8(3):59-74. doi: 10.11648/j.ijema.20200803.13

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@article{10.11648/j.ijema.20200803.13,
  author = {Barnabas Morakinyo and Samantha Lavender and Victor Abbott},
  title = {Retrieval of Land Surface Temperature from Earth Observation Satellites for Gas Flaring Sites in the Niger Delta, Nigeria},
  journal = {International Journal of Environmental Monitoring and Analysis},
  volume = {8},
  number = {3},
  pages = {59-74},
  doi = {10.11648/j.ijema.20200803.13},
  url = {https://doi.org/10.11648/j.ijema.20200803.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20200803.13},
  abstract = {This research investigates the recording of Land Surface Temperature (LST) by Earth Observation (EO) Satellites for four gas flaring sites in Rivers State, Nigeria. Six Landsat 5 Thematic Mapper (TM) and Eleven Landsat 7 Enhanced Thematic Mapper Plus (ETM+) from 17 January 1986 to 08 March 2013 with u), downwelling radiance (Ld) and transmittance (τ)] of Landsat data respectively. The emissivity (ε) for each site is estimated by using standard values for determined land surface cover from Look Up Table (LUT). The correction obtained from DOS method was applied to the computed reflectance to get the atmospherically corrected reflectance that was used for the classification of land cover. The Lu, Ld and τ obtained were applied to the calibrated at-sensor radiance band 6 (high gain) data to compute the surface-leaving radiance (Lλ) with the εvalues obtained for each site. The Planck equation was inverted using the calibration constants to derive LST. Six range of LST values were retrieved for each flaring site, with Bonny Liquefied Natural Gas (LNG) Plant recorded the highest LST (345.0 K) and Umudioga Flow Station with the lowest (293.0 K). LST retrieved from both sensors for the flare hotspots are the highest values compared to other locations within the processing sites, which was clearly shown through Geospatial Information System (GIS) spatial analysis and the transects plots. Furthermore, the closer is the distance to the flare, the higher is the temperature and vice versa. Based on these results, it can be concluded that satellite based sensors, such as Landsat TM and ETM+, have the ability to record LST at gas flaring sites in the Niger Delta.},
 year = {2020}
}

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TY  - JOUR
T1  - Retrieval of Land Surface Temperature from Earth Observation Satellites for Gas Flaring Sites in the Niger Delta, Nigeria
AU  - Barnabas Morakinyo
AU  - Samantha Lavender
AU  - Victor Abbott
Y1  - 2020/08/27
PY  - 2020
N1  - https://doi.org/10.11648/j.ijema.20200803.13
DO  - 10.11648/j.ijema.20200803.13
T2  - International Journal of Environmental Monitoring and Analysis
JF  - International Journal of Environmental Monitoring and Analysis
JO  - International Journal of Environmental Monitoring and Analysis
SP  - 59
EP  - 74
PB  - Science Publishing Group
SN  - 2328-7667
UR  - https://doi.org/10.11648/j.ijema.20200803.13
AB  - This research investigates the recording of Land Surface Temperature (LST) by Earth Observation (EO) Satellites for four gas flaring sites in Rivers State, Nigeria. Six Landsat 5 Thematic Mapper (TM) and Eleven Landsat 7 Enhanced Thematic Mapper Plus (ETM+) from 17 January 1986 to 08 March 2013 with u), downwelling radiance (Ld) and transmittance (τ)] of Landsat data respectively. The emissivity (ε) for each site is estimated by using standard values for determined land surface cover from Look Up Table (LUT). The correction obtained from DOS method was applied to the computed reflectance to get the atmospherically corrected reflectance that was used for the classification of land cover. The Lu, Ld and τ obtained were applied to the calibrated at-sensor radiance band 6 (high gain) data to compute the surface-leaving radiance (Lλ) with the εvalues obtained for each site. The Planck equation was inverted using the calibration constants to derive LST. Six range of LST values were retrieved for each flaring site, with Bonny Liquefied Natural Gas (LNG) Plant recorded the highest LST (345.0 K) and Umudioga Flow Station with the lowest (293.0 K). LST retrieved from both sensors for the flare hotspots are the highest values compared to other locations within the processing sites, which was clearly shown through Geospatial Information System (GIS) spatial analysis and the transects plots. Furthermore, the closer is the distance to the flare, the higher is the temperature and vice versa. Based on these results, it can be concluded that satellite based sensors, such as Landsat TM and ETM+, have the ability to record LST at gas flaring sites in the Niger Delta.
VL  - 8
IS  - 3
ER  -

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